模拟退火算法解决路径优化 源代码

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1、模拟退火算法解决路径优化的源代码我有simulatedannealingwithmetropolies(MonteCarlo)做的一个项目的代码，你要看看么？voidanneal(intnparam,intnstep,intnstep_per_block,doublet0,constdouble*param_in,doublecost_in,double*params_out,double*cost_out){intnblock;intstep;intblock;intnactive;intrank;intn_accepted

2、=0;inti,j,n;doublecost_current,cost_trial;int*param_index;double*param_current;double*param_trial;double*Q;double*S;double*u;double*dp;double*A;FILE*fp_log_file;charfname[FILENAME_MAX];doubletemp=t0;doubletempmax=temp;doubleebar,evar,emin,eta,specific_heat;doubledel

3、ta;doublechi=0.8;//Annealingscheduledoublechi_s=3.0;//Vanderbilt/Louie'growthfactor'doublerm;doubleroot3=sqrt(3.0);doublep=0.02/sqrt(3.0);//maxsizeofannealingstepparam_current=newdouble[nparam];param_trial=newdouble[nparam];cost_current=cost_in;MPI_Comm_rank(MPI_COM

4、M_WORLD,&rank);sprintf(fname,"a_%4.4d.log",rank);fp_log_file=fopen(fname,"a");if(fp_log_file==(FILE*)NULL)errorMessage("fopen(log)failed");//Workoutthenumberofactiveparameters,andsetupthe//indextableoftheactiveparameters.//Notethatthecompletearrayofparameters(para

5、m_trial)must//beusedtoevaluatethecostfunction.nactive=0;for(n=0;n

6、ethestepdistributionmatrixQ_ijQ=newdouble[nactive*nactive];S=newdouble[nactive*nactive];u=newdouble[nactive];dp=newdouble[nactive];A=newdouble[nactive];double*Qtmp;Qtmp=newdouble[nactive*nactive];for(i=0;i

7、+j]=p*delta*param_current[param_index[j]];}}//carryoutannealingpointsnblock=nstep/nstep_per_block;rm=1.0/(double)nstep_per_block;for(block=0;block

8、diagonal.temp=chi*temp;for(i=0;i